{"title":"加权分页的原始对偶随机化算法","authors":"N. Bansal, Niv Buchbinder, J. Naor","doi":"10.1145/2339123.2339126","DOIUrl":null,"url":null,"abstract":"In the weighted paging problem there is a weight (cost) for fetching each page into the cache. We design a randomized O(log k) -competitive online algorithm for the weighted paging problem, where k is the cache size. This is the first randomized o(k)-competitive algorithm and its competitiveness matches the known lower bound on the problem. More generally, we design an O(log(k/(k - h + I)))-competitive online algorithm for the version of the. problem where, the online algorithm has-cache size k and the online algorithm has cache size h les k. Weighted paging is a special case (weighted star metric) of the well known k-server problem for which it is a major open question whether randomization can be useful in obtaining sub-linear competitive algorithms. Therefore, abstracting and extending the insights from paging is a key step in the resolution of the k-server problem. Our solution for the weighted paging problem is based on a two-step approach. In the first step we obtain an O(log k)-competitive fractional algorithm which is based on a novel online primal-dual approach. In the second step we. obtain a randomized algorithm by rounding online the fractional solution to an actual distribution on integral cache, solutions. We conclude with a randomized O(log N)-competitive algorithm for the well studied Metrical Task System problem (MTS) on a metric defined by a weighted star on N leaves, improving upon a previous O(log2 N)-competitive algorithm of Blum et al. [9].","PeriodicalId":197431,"journal":{"name":"48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"166","resultStr":"{\"title\":\"A primal-dual randomized algorithm for weighted paging\",\"authors\":\"N. Bansal, Niv Buchbinder, J. Naor\",\"doi\":\"10.1145/2339123.2339126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the weighted paging problem there is a weight (cost) for fetching each page into the cache. We design a randomized O(log k) -competitive online algorithm for the weighted paging problem, where k is the cache size. This is the first randomized o(k)-competitive algorithm and its competitiveness matches the known lower bound on the problem. More generally, we design an O(log(k/(k - h + I)))-competitive online algorithm for the version of the. problem where, the online algorithm has-cache size k and the online algorithm has cache size h les k. Weighted paging is a special case (weighted star metric) of the well known k-server problem for which it is a major open question whether randomization can be useful in obtaining sub-linear competitive algorithms. Therefore, abstracting and extending the insights from paging is a key step in the resolution of the k-server problem. Our solution for the weighted paging problem is based on a two-step approach. In the first step we obtain an O(log k)-competitive fractional algorithm which is based on a novel online primal-dual approach. In the second step we. obtain a randomized algorithm by rounding online the fractional solution to an actual distribution on integral cache, solutions. We conclude with a randomized O(log N)-competitive algorithm for the well studied Metrical Task System problem (MTS) on a metric defined by a weighted star on N leaves, improving upon a previous O(log2 N)-competitive algorithm of Blum et al. [9].\",\"PeriodicalId\":197431,\"journal\":{\"name\":\"48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"166\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2339123.2339126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2339123.2339126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A primal-dual randomized algorithm for weighted paging
In the weighted paging problem there is a weight (cost) for fetching each page into the cache. We design a randomized O(log k) -competitive online algorithm for the weighted paging problem, where k is the cache size. This is the first randomized o(k)-competitive algorithm and its competitiveness matches the known lower bound on the problem. More generally, we design an O(log(k/(k - h + I)))-competitive online algorithm for the version of the. problem where, the online algorithm has-cache size k and the online algorithm has cache size h les k. Weighted paging is a special case (weighted star metric) of the well known k-server problem for which it is a major open question whether randomization can be useful in obtaining sub-linear competitive algorithms. Therefore, abstracting and extending the insights from paging is a key step in the resolution of the k-server problem. Our solution for the weighted paging problem is based on a two-step approach. In the first step we obtain an O(log k)-competitive fractional algorithm which is based on a novel online primal-dual approach. In the second step we. obtain a randomized algorithm by rounding online the fractional solution to an actual distribution on integral cache, solutions. We conclude with a randomized O(log N)-competitive algorithm for the well studied Metrical Task System problem (MTS) on a metric defined by a weighted star on N leaves, improving upon a previous O(log2 N)-competitive algorithm of Blum et al. [9].